"Lean Manufacturing: Context, Practice Bundles, and Performance"

Rachna Shah and Peter Ward

Journal of Operations Management

2003, 21, 129-149

Using existing data from the Industry Week U.S. Census of Manufacturers, the authors of this article examined the influence of plant size, plant age, and unionization on implementation of 22 manufacturing practices (JIT/continuous flow production; pull system; cellular manufacturing; cycle time reduction; focused factory production systems; agile manufacturing strategies; quick changeover techniques; bottleneck/constraint removal; reengineered production processes; predictive or preventive maintenance; maintenance optimization; safety improvement programs; planning and scheduling strategies; new process equipment or technologies; competitive benchmarking; quality management programs; total quality management; process capability measurements; formal continuous improvement program; self-directed work teams; flexible cross-functional workforce) that are key facets of Lean manufacturing. They also examined the effects of 4 "Lean bundles" (JIT, TQM, TPM, and HRM)—combined from the above 22 manufacturing practices-on plant performance.

The primary results were:

1. Larger manufacturers were more likely to implement 20 of the 22 manufacturing practices (there was no significant difference for cross-functional workforce and quality management programs);
2. For age of the plants, there was no difference between older and newer plants on 14 of the manufacturing practices. Older plants were statistically less likely to implement 5 of the practices (cross-functional workforce; JIT/continuous flow production; maintenance optimization; reengineered production process; and self-directed work teams) and statistically more likely to implement 3 of the practices (planning and scheduling strategies; safety improvement programs; and total quality management);
3. Unionization had no influence on implementation of 16 of the manufacturing practices. Unionized plants were less likely to implement cellular manufacturing, cross-functional workforce, cycle time reduction, maintenance optimization, process capability measurements, and self-directed work teams;
4. JIT, TTQM, TPM, and HRM were all found to positively, and additively, influence performance variables. Overall, use of these practices explained 27.7% of the variance in operational performance of the plants, with JIT having the greatest influence on performance.

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